Project AiAi.care

About

AiAi.care charity is working to reduce Tuberculosis 👾 and Lung Cancer screening time and screening costs by teaching computers to "see" and interpret chest X-rays how a human Radiologist would.

We are using 700,000 labeled chest X-Rays dataset + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi.care CAD will be distributed for free to emerging nations and charitable hospitals everywhere 🌏

Why Tuberculosis Algorithm

One in four people are exposed to M. Tuberculosis bacterium, but it does not become active TB unless mixed with malnutrition and overcrowding. These two factors have earned TB the nickname "disease of poverty".
Emerging nations have 12x fewer Radiologists compared to developed world, so TB patients often remain undetected while continuing to spread the bacterium further through air (coughing, sneezing, spitting). In recent years Tuberculosis is massively resurgent with 8.6 million new cases of active TB diagnosed worldwide in 2012. India accounted for a record 2.76 million new cases in 2016. A lot of these cases are MDR (Multi-Drug Resistant) TB strain.
AiAi's free TB screening tool will help emerging nations overcome shortage of Radiologists by screening X-rays within 45 seconds of capture. Early results show that our algo can potentially deliver expert-panel grade TB screening capabilities to underserved regions.

Why Lung Cancer Algorithm

When it comes to cancer, early detection delivers a huge delta in survival rates compared to late detection. Unfortunately, Lung Cancer is mostly asymptomatic in earlier stages so detections in developing countries happen around Stage (III A). This late detection causes more people to die of lung cancer than of colon, breast, and prostate cancers combined.

Cancer Stage:

I.II.III.IV.

5-Yr Survival:

47%26%8%2%

71% of lung cancers detected in chest X-Rays were visible in retrospect on previous imaging studies. Furthermore, a 1999 NIH long-term study of American Radiologists found that 19% missed lung cancers present in current chest X-Rays. These numbers may be more stark for developing nations where X-Rays are read by Primary Care Physians (PCP) instead of Radiologists.

Herein lies a 5X life-saving opportunity for early detection: We propose that a Machine-Learning screening tool with class leading sensitivity and specificity can help reduce missed-diagnose opportunities, and as a result improve survival rates 5X through early detection.

Price of Commercial 💸 CADs

An FDA-approved commercial CADe / CADx package costs $50,000 per year for low volume radiology facilities that consult <20 patients per day. A typical large hospital license with hundreds of studies per day costs $500,000🧐 per year or more.

These costs are entirely out of reach for developing countries and charitable hospitals. This is why we are building AiAi to provide a free 🗽 FDA-approved, open-source alternative to the world.